ABSTRACT Alzheimer's Disease (AD) is a neurodegenerative disease and common cause of dementia in elderly individuals. The loss of memory, inability to learn, decreased language function, among other neurological deficits, affects social functioning, and are catastrophic to maintaining daily life. The progression of AD eventually causes death within 5-10 years, and during this time the burden of patient care falls on an already stressed healthcare system. In 2017, it is estimated that AD cost the US $259 billion and by 2050 estimates could be as much as $1.1 trillion. The main focus of our ongoing R01CA218144 project is to map the intratumoral and intertumoral heterogeneities of glioblastoma brain tumors at molecular, cellular, and tissue scales using whole brain samples aligned to clinical MRI scans. This supplement, in response to NOT-AG-18-008, looks to extend this technology into the diagnosis and treatment of AD. Central Hypothesis: Microscopic cytological features of Alzheimer?s disease are detectable and quantifiable with macroscopic MR imaging. Rationale: To date, Radiological-Pathological (Rad-Path) imaging studies of AD have been extremely limited due to the difficulty in recruiting patients for both imaging and brain donation. The departments of radiology and pathology at the Medical College of Wisconsin have an ongoing brain donation program for patients with glioblastoma that enables us to correlate imaging findings to the underlying pathology using whole brain tissue samples. This extensive tissue and imaging bank has been used to validate imaging technology by combining complementary radiographic and pathological information. This growing one-of-a-kind dataset will be extended to include the recruitment of patients with AD participating in the Alzheimer?s Connectome Project. Our preliminary results from our ongoing brain cancer studies suggest that hidden untapped information within the macroscopic imaging can be used to predict the presence of invasive tumor. Completion of these aims may establish an additional imaging biomarker for predicting AD pathology, and as efforts move forward to personalize treatment, this information will be invaluable in the clinical setting. !